Technical Program Manager - Feed and Video Ranking and Recommendations

Facebook's Feed and Video Ranking & Recommendation team seeks a Technical Program Manager (TPM) to lead complex, large-scale programs advancing the state-of-the-art in machine learning and AI systems for content ranking and recommendation. In this high-impact role, you will collaborate across engineering, research, product, hardware, and data center teams to design, build, and scale the foundational infrastructure and algorithms that power Meta's core user experiences.You will drive the end-to-end integration of new ML models, hardware, and infra stack-from initial design validation through production deployment-focusing on reliability, efficiency, and scalability. This includes developing repeatable frameworks for onboarding new ML platforms, ensuring robust execution, and proactively resolving technical and organizational challenges to maintain project momentum. You will leverage your technical acumen and business insight to streamline onboarding of new AI hardware and ML platforms into Meta's core ranking and recommendation infrastructure, championing best practices and driving impactful outcomes that advance Meta's AI capabilities.

Technical Program Manager - Feed and Video Ranking and Recommendations Responsibilities:

• Lead and align cross-functional program teams to deliver on ML/AI infrastructure goals, ensuring clarity of objectives and accountability
• Partner with engineering, hardware, data center, and research teams to define program requirements, prioritize initiatives, and shape the roadmap for ML/AI infra and platform scaling
• Drive technical strategy and execution for onboarding and scaling new AI hardware (GPUs, accelerators) and distributed ML systems, including LLMs and GenAI workloads
• Develop and implement communication strategies to proactively share program status, challenges, and risks with stakeholders at all levels
• Manage cross-functional dependencies and risks, adjusting scope, timeline, and resources to ensure successful delivery of ML/AI infra programs
• Lead the end-to-end lifecycle of ML/AI infra programs: technical analysis, design, development, testing, deployment, and post-launch support
• Establish and track key metrics, benchmarks, and performance indicators for ML/AI infra, driving accountability and continuous improvement
• Anticipate and address complex, long-term infrastructure challenges in partnership with engineering and research leaders
• Drive product and infra strategy to support Meta's AI/ML initiatives, including responsible and privacy-preserving AI
• Champion process improvements and automation to streamline workflows and reduce manual effort across ML/AI infra teams
• Foster innovation, reliability, and efficiency in scaling ML/AI systems at Meta
• Commitment to scaling infrastructure for large-scale ML/AI systems, including privacy, security, and responsible AI practices

• Bachelor's degree in Computer Science, Electrical Engineering, or related technical field, or equivalent experience
• 12+ years of experience in software engineering, hardware engineering, systems engineering, or technical product/program management, with a focus on ML/AI systems or infrastructure
• Knowledge of software and hardware development for large-scale ML/AI platforms, including distributed training, inference, and hardware readiness
• Proven experience delivering complex ML/AI technology programs from inception to production at scale
• Demonstrated ability to define and optimize engineering processes for ML/AI infra, including onboarding, reliability, and efficiency
• Demonstrated analytical and problem-solving skills for large-scale ML/AI systems
• Experience building and influencing cross-functional relationships across engineering, research, hardware, and product teams
• Experience defining strategic direction and identifying new opportunities for impact in ML/AI infra and platforms
• Effective communication skills, with experience influencing executive leadership and technical management teams
• Strong understanding of large language models, machine learning, and scaling distributed systems for AI workloads

• Experience with ML/AI infra platforms (e.g., PyTorch, TensorFlow, distributed training frameworks)
• Experience with onboarding and scaling new hardware platforms (GPUs, accelerators) for ML/AI workloads
• Experience in open source ML/AI platform development and community engagement
• Experience driving responsible and privacy-preserving AI initiatives
• Experience in technical leadership roles for ML/AI infra programs at planetary scale